Technical Program Manager – VLSI

NVIDIA•Us, CA

6d•Hybrid

About The Position

NVIDIA is looking for a Technical Program Manager with a strong engineering foundation and a passion for automation to join its VLSI Engineering organization. This role serves as the central program management function, providing structure and insight to deliver world-class silicon. The Technical Program Manager will leverage Agentic AI and Python to automate project management methodologies, creating a self-governing infrastructure for silicon roadmaps. This position bridges the gap between traditional project management and software development, aiming to automate routine project management tasks and integrate engineering data into real-time program health dashboards.

Requirements

BS in Computer Science, Computer Engineering, or a related field or equivalent experience (Masters preferred).
5+ years of engineering experience with 2+ years of project or program management experience, backed by a solid technical/engineering foundation.
Proficiency in Python is mandatory.
Robust full-stack and DevOps experience (Kubernetes, containerization, cloud infrastructure).
Comfortable using AI-assisted coding environments.
Proven experience or strong interest in deploying Large Language Models (LLMs) and agentic frameworks to solve operational bottlenecks.
Deep understanding of organizational workflow maturity—the ability to identify process gaps, add necessary telemetry, and engineer the transition from manual playbooks to reliable code.
Comfortable working in a fast-paced environment where you must maintain composure while embracing rapid changes in AI technology.

Nice To Haves

Prior experience in Hardware Project Management or exposure to the ASIC/SoC development lifecycle.
Advanced experience with API integrations between project management tools (e.g., Smartsheet, Jira) and custom full-stack applications.
Background in data engineering or building automated KPI dashboards.

Responsibilities

Translate complex VLSI project management methodologies into highly scalable, full-stack software solutions.
Develop, containerize (e.g., Kubernetes, Docker), and maintain AI-driven agents to automate routine project management tasks such as schedule tracking, resource mapping, and dependency mapping.
Partner with VLSI Program Managers and Engineering Leads to assess work processes, systematically upgrading them from undocumented, manual tasks into measured baselines, and ultimately into robust, self-improving automated systems.
Use Python, modern web frameworks, and AI-assisted environments (like Cursor, Claude, Codex, etc.) to build internal tools and API integrations that seamlessly ingest lab and engineering data into real-time program health dashboards.
Reduce manual overhead for technical leads by implementing CI/CD pipelines and DevOps best practices for internal project management tooling.